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Reference architecture design for machine learning supported cybersecurity systems
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2024-12-31
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Abstract
Cybersecurity is a critical aspect of software-intensive systems, and machine learning has the potential to enhance its effectiveness. However, the design of cybersecurity systems and the use of machine learning have been carried out in isolation, leading to potential gaps in overall security. This chapter addresses this issue by presenting a reference architecture design for machine learning-supported cybersecurity systems. The design integrates engineering and machine learning perspectives, resulting in a holistic approach that enhances the security of software-intensive systems. The chapter presents the results of a domain analysis and architecture design stage. It demonstrates the effectiveness of the proposed reference architecture through a synthesis of architecture design approaches and machine learning models used in the cybersecurity domain. The resulting solution approach is holistic, combining engineering design and machine learning perspectives. The proposed reference architecture, built from synthesized design approaches and machine learning models in the cybersecurity domain, is effective for machine learning-supported cyber-secure systems.